Variable selection in heteroscedastic discriminant analysis

L. Paul Fatti, Douglas M. Hawkins

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


The likelihood ratio test statistic for the identity in means and covariance matrices of k normal populations has a well-known step-down decomposition measuring the contribution of each component of the vector observation. This decomposition in turn gives rise to three components testing the residual homo-scedasticity of each variable, the parallelism of its regression on its predecessors, and the identity of location. A variety of uses of this decomposition in selecting variables is proposed. © 1976 Taylor & Francis Group, LLC.

Original languageEnglish (US)
Pages (from-to)494-500
Number of pages7
JournalJournal of the American Statistical Association
Issue number394
StatePublished - 1986


  • Combining independent tests
  • Likelihood ratio


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